Question: I'm looking for a solution that streamlines data analysis and simplifies IT in scientific research environments.

If you need to streamline data analysis and make IT easier in a scientific research setting, Enthought is a good choice. It offers a full digital transformation platform for scientific R&D labs. The Enthought Edge cloud-native computational platform offers direct access to and analysis of structured and unstructured data, deployment of custom applications and self-service management of compute resources and cloud expenses. That can help scientists speed up discovery, cut costs and deliver business results.

Another good option is KNIME, an open-source data analysis tool that requires little programming expertise. It has a lot of features, including a visual workflow builder, data access and transformation tools for more than 300 sources, a variety of analytical techniques, secure deployment and interactive data apps. KNIME is good for a wide range of users, and it offers free analytics with more features available through the KNIME Hub.

Altair RapidMiner is another option, particularly if your organization wants to automate operations without major changes to its infrastructure. It's an end-to-end data analytics and AI platform with code-free to code-friendly interfaces, interactive decision trees and real-time data processing and visualization. That makes it a good choice for teams in many industries who want to streamline their data analytics workflows and tap into the power of AI and machine learning.

Last, Anaconda is a powerful data science and AI development ecosystem that's good for industries like financial services, health care and manufacturing. It includes collaboration tools, industry-specific AI tools, one-click deployment and access to a vast library of open-source software. Anaconda can help operations run better and decisions be made better with scalable and secure tools for data scientists and the companies that employ them.